Protein-membrane interactions: sensing and generating curvature.

Biological membranes are integral cellular structures that can be curved into various geometries. These curved structures are abundant in cells as they are essential for various physiological processes. However, curved membranes are inherently unstable, especially on nanometer length scales. To stabilize curved membranes, cells can utilize proteins that sense and generate membrane curvature. In this review, we summarize recent research that has advanced our understanding of interactions between proteins and curved membrane surfaces, as well as work that has expanded our ability to study curvature sensing and generation. Additionally, we look at specific examples of cellular processes that require membrane curvature, such as neurotransmission, clathrin-mediated endocytosis (CME), and organelle biogenesis.

Correction: A continuum membrane model can predict curvature sensing by helix insertion.

Correction for 'A continuum membrane model can predict curvature sensing by helix insertion' by Yiben Fu et al., Soft Matter, 2021, 17, 10649-10663, DOI: 10.1039/D1SM01333E.

Clathrin senses membrane curvature.

The ability of proteins to assemble at sites of high membrane curvature is essential to diverse membrane remodeling processes, including clathrin-mediated endocytosis. Multiple adaptor proteins within the clathrin pathway have been shown to sense regions of high membrane curvature, leading to local recruitment of the clathrin coat. Because clathrin triskelia do not bind to the membrane directly, it has remained unclear whether the clathrin coat plays an active role in sensing membrane curvature or is passively recruited by adaptor proteins. Using a synthetic tag to assemble clathrin directly on membrane surfaces, here we show that clathrin is a strong sensor of membrane curvature, comparable with previously studied adaptor proteins. Interestingly, this sensitivity arises from clathrin assembly rather than from the properties of unassembled triskelia, suggesting that triskelia have preferred angles of interaction, as predicted by earlier structural data. Furthermore, when clathrin is recruited by adaptors, its curvature sensitivity is amplified by 2- to 10-fold, such that the resulting protein complex is up to 100 times more likely to assemble on a highly curved surface compared with a flatter one. This exquisite sensitivity points to a synergistic relationship between the coat and its adaptor proteins, which enables clathrin to pinpoint sites of high membrane curvature, an essential step in ensuring robust membrane traffic. More broadly, these findings suggest that protein networks, rather than individual protein domains, are likely the most potent drivers of membrane curvature sensing.

A continuum membrane model can predict curvature sensing by helix insertion.

Protein domains, such as ENTH (epsin N-terminal homology) and BAR (bin/amphiphysin/rvs), contain amphipathic helices that drive preferential binding to curved membranes. However, predicting how the physical parameters of these domains control this 'curvature sensing' behavior is challenging due to the local membrane deformations generated by the nanoscopic helix on the surface of a large sphere. We here use a deformable continuum model that accounts for the physical properties of the membrane and the helix insertion to predict curvature sensing behavior, with direct validation against multiple experimental datasets. We show that the insertion can be modeled as a local change to the membrane's spontaneous curvature, cins0, producing excellent agreement with the energetics extracted from experiments on ENTH binding to vesicles and cylinders, and of ArfGAP helices to vesicles. For small vesicles with high curvature, the insertion lowers the membrane energy by relieving strain on a membrane that is far from its preferred curvature of zero. For larger vesicles, however, the insertion has the inverse effect, de-stabilizing the membrane by introducing more strain. We formulate here an empirical expression that accurately captures numerically calculated membrane energies as a function of both basic membrane properties (bending modulus κ and radius R) as well as stresses applied by the inserted helix (cins0 and area Ains). We therefore predict how these physical parameters will alter the energetics of helix binding to curved vesicles, which is an essential step in understanding their localization dynamics during membrane remodeling processes.

Molecular Mechanisms of Membrane Curvature Sensing by a Disordered Protein.

The ability of proteins to sense membrane curvature is essential for the initiation and assembly of curved membrane structures. Established mechanisms of curvature sensing rely on proteins with specific structural features. In contrast, it has recently been discovered that intrinsically disordered proteins, which lack a defined three-dimensional fold, can also be potent sensors of membrane curvature. How can an unstructured protein sense the structure of the membrane surface? Many disordered proteins that associate with membranes have two key physical features: a high degree of conformational entropy and a high net negative charge. Binding of such proteins to membrane surfaces results simultaneously in a decrease in conformational entropy and an increase in electrostatic repulsion by anionic lipids. Here we show that each of these effects gives rise to a distinct mechanism of curvature sensing. Specifically, as the curvature of the membrane increases, the steric hindrance between the disordered protein and membrane is reduced, leading to an increase in chain entropy. At the same time, increasing membrane curvature increases the average separation between anionic amino acids and lipids, creating an electrostatic preference for curved membranes. Using quantitative imaging of membrane vesicles, our results demonstrate that long disordered amino acid chains with low net charge sense curvature predominately through the entropic mechanism. In contrast, shorter, more highly charged amino acid chains rely largely on the electrostatic mechanism. These findings provide a roadmap for predicting and testing the curvature sensitivity of the large and diverse set of disordered proteins that function at cellular membranes.

Structured and intrinsically disordered domains within Amphiphysin1 work together to sense and drive membrane curvature.

Cellular membranes undergo remodeling during many cellular processes including endocytosis, cytoskeletal protrusion, and organelle biogenesis. During these events, specialized proteins sense and amplify fluctuations in membrane curvature to create stably curved architectures. Amphiphysin1 is a multi-domain protein containing an N-terminal crescent-shaped BAR (Bin/Amphiphysin/Rvs) domain and a C-terminal domain that is largely disordered. When studied in isolation, the BAR domain of Amphiphysin1 senses membrane curvature and generates membrane tubules. However, the disordered domain has been largely overlooked in these studies. Interestingly, our recent work has demonstrated that the disordered domain is capable of substantially amplifying the membrane remodeling ability of the BAR domain. However, the physical mechanisms responsible for these effects are presently unclear. Here we elucidated the functional role of the disordered domain by gradually truncating it, creating a family of mutant proteins, each of which contained the BAR domain and a fraction of the disordered domain. Using quantitative fluorescence and electron microscopy, our results indicate that the disordered domain contributes to membrane remodeling by making it more difficult for the protein to bind to and assemble on flat membrane surfaces. Specifically, we found that the disordered domain began to significantly impact membrane remodeling when its projected area exceeded that of the BAR domain. Once this threshold was crossed, steric interactions with the membrane surface and with neighboring disordered domains gave rise to increased curvature sensing and membrane vesiculation, respectively. These findings provide insight into the synergy between structured and disordered domains, each of which play important biophysical roles in membrane remodeling.

Self-diffusion of a highly concentrated monoclonal antibody by fluorescence correlation spectroscopy: insight into protein-protein interactions and self-association.

The dynamic behavior of monoclonal antibodies (mAbs) at high concentration provides insight into protein microstructure and protein-protein interactions (PPI) that influence solution viscosity and protein stability. At high concentration, interpretation of the collective-diffusion coefficient Dc, as determined by dynamic light scattering (DLS), is highly challenging given the complex hydrodynamics and PPI at close spacings. In contrast, self-diffusion of a tracer particle by Brownian motion is simpler to understand. Herein, we develop fluorescence correlation spectroscopy (FCS) for the measurement of the long-time self-diffusion of mAb2 over a wide range of concentrations and viscosities in multiple co-solute formulations with varying PPI. The normalized self-diffusion coefficient D0/Ds (equal to the microscopic relative viscosity ηeff/η0) was found to be smaller than η/η0. Smaller ratios of the microscopic to macroscopic viscosity (ηeff/η) are attributed to a combination of weaker PPI and less self-association. The interaction parameters extracted from fits of D0/Ds with a length scale dependent viscosity model agree with previous measurements of PPI by SLS and SAXS. Trends in the degree of self-association, estimated from ηeff/η with a microviscosity model, are consistent with oligomer sizes measured by SLS. Finally, measurements of collective diffusion and osmotic compressibility were combined with FCS data to demonstrate that the changes in self-diffusion between formulations are due primarily to changes in the protein-protein friction in these systems, and not to protein-solvent friction. Thus, FCS is a robust and accessible technique for measuring mAb self-diffusion, and, by extension, microviscosity, PPI and self-association that govern mAb solution dynamics.

The 2018 biomembrane curvature and remodeling roadmap.

The importance of curvature as a structural feature of biological membranes has been recognized for many years and has fascinated scientists from a wide range of different backgrounds. On the one hand, changes in membrane morphology are involved in a plethora of phenomena involving the plasma membrane of eukaryotic cells, including endo- and exocytosis, phagocytosis and filopodia formation. On the other hand, a multitude of intracellular processes at the level of organelles rely on generation, modulation, and maintenance of membrane curvature to maintain the organelle shape and functionality. The contribution of biophysicists and biologists is essential for shedding light on the mechanistic understanding and quantification of these processes. Given the vast complexity of phenomena and mechanisms involved in the coupling between membrane shape and function, it is not always clear in what direction to advance to eventually arrive at an exhaustive understanding of this important research area. The 2018 Biomembrane Curvature and Remodeling Roadmap of Journal of Physics D: Applied Physics addresses this need for clarity and is intended to provide guidance both for students who have just entered the field as well as established scientists who would like to improve their orientation within this fascinating area.

Crowding-Induced Mixing Behavior of Lipid Bilayers: Examination of Mixing Energy, Phase, Packing Geometry, and Reversibility.

In an effort to develop a general thermodynamic model from first-principles to describe the mixing behavior of lipid membranes, we examined lipid mixing induced by targeted binding of small (Green Fluorescent Protein (GFP)) and large (nanolipoprotein particles (NLPs)) structures to specific phases of phase-separated lipid bilayers. Phases were targeted by incorporation of phase-partitioning iminodiacetic acid (IDA)-functionalized lipids into ternary lipid mixtures consisting of DPPC, DOPC, and cholesterol. GFP and NLPs, containing histidine tags, bound the IDA portion of these lipids via a metal, Cu(2+), chelating mechanism. In giant unilamellar vesicles (GUVs), GFP and NLPs bound to the Lo domains of bilayers containing DPIDA, and bound to the Ld region of bilayers containing DOIDA. At sufficiently large concentrations of DPIDA or DOIDA, lipid mixing was induced by bound GFP and NLPs. The validity of the thermodynamic model was confirmed when it was found that the statistical mixing distribution as a function of crowding energy for smaller GFP and larger NLPs collapsed to the same trend line for each GUV composition. Moreover, results of this analysis show that the free energy of mixing for a ternary lipid bilayer consisting of DOPC, DPPC, and cholesterol varied from 7.9 × 10(-22) to 1.5 × 10(-20) J/lipid at the compositions observed, decreasing as the relative cholesterol concentration was increased. It was discovered that there appears to be a maximum packing density, and associated maximum crowding pressure, of the NLPs, suggestive of circular packing. A similarity in mixing induced by NLP1 and NLP3 despite large difference in projected areas was analytically consistent with monovalent (one histidine tag) versus divalent (two histidine tags) surface interactions, respectively. In addition to GUVs, binding and induced mixing behavior of NLPs was also observed on planar, supported lipid multibilayers. The mixing process was reversible, with Lo domains reappearing after addition of EDTA for NLP removal.

Analysis of lipid phase behavior and protein conformational changes in nanolipoprotein particles upon entrapment in sol-gel-derived silica.

The entrapment of nanolipoprotein particles (NLPs) and liposomes in transparent, nanoporous silica gel derived from the precursor tetramethylorthosilicate was investigated. NLPs are discoidal patches of lipid bilayer that are belted by amphiphilic scaffold proteins and have an average thickness of 5 nm. The NLPs in this work had a diameter of roughly 15 nm and utilized membrane scaffold protein (MSP), a genetically altered variant of apolipoprotein A-I. Liposomes have previously been examined inside of silica sol-gels and have been shown to exhibit instability. This is attributed to their size (∼150 nm) and altered structure and constrained lipid dynamics upon entrapment within the nanometer-scale pores (5-50 nm) of the silica gel. By contrast, the dimensional match of NLPs with the intrinsic pore sizes of silica gel opens the possibility for their entrapment without disruption. Here we demonstrate that NLPs are more compatible with the nanometer-scale size of the porous environment by analysis of lipid phase behavior via fluorescence anisotropy and analysis of scaffold protein secondary structure via circular dichroism spectroscopy. Our results showed that the lipid phase behavior of NLPs entrapped inside of silica gel display closer resemblance to its solution behavior, more so than liposomes, and that the MSP in the NLPs maintain the high degree of α-helix secondary structure associated with functional protein-lipid interactions after entrapment. We also examined the effects of residual methanol on lipid phase behavior and the size of NLPs and found that it exerts different influences in solution and in silica gel; unlike in free solution, silica entrapment may be inhibiting NLP size increase and/or aggregation. These findings set precedence for a bioinorganic hybrid nanomaterial that could incorporate functional integral membrane proteins.

Fermentation temperature modulates phosphatidylethanolamine and phosphatidylinositol levels in the cell membrane of Saccharomyces cerevisiae.

During alcoholic fermentation, Saccharomyces cerevisiae is exposed to a host of environmental and physiological stresses. Extremes of fermentation temperature have previously been demonstrated to induce fermentation arrest under growth conditions that would otherwise result in complete sugar utilization at "normal" temperatures and nutrient levels. Fermentations were carried out at 15°C, 25°C, and 35°C in a defined high-sugar medium using three Saccharomyces cerevisiae strains with diverse fermentation characteristics. The lipid composition of these strains was analyzed at two fermentation stages, when ethanol levels were low early in stationary phase and in late stationary phase at high ethanol concentrations. Several lipids exhibited dramatic differences in membrane concentration in a temperature-dependent manner. Principal component analysis (PCA) was used as a tool to elucidate correlations between specific lipid species and fermentation temperature for each yeast strain. Fermentations carried out at 35°C exhibited very high concentrations of several phosphatidylinositol species, whereas at 15°C these yeast strains exhibited higher levels of phosphatidylethanolamine and phosphatidylcholine species with medium-chain fatty acids. Furthermore, membrane concentrations of ergosterol were highest in the yeast strain that experienced stuck fermentations at all three temperatures. Fluorescence anisotropy measurements of yeast cell membrane fluidity during fermentation were carried out using the lipophilic fluorophore diphenylhexatriene. These measurements demonstrate that the changes in the lipid composition of these yeast strains across the range of fermentation temperatures used in this study did not significantly affect cell membrane fluidity. However, the results from this study indicate that fermenting S. cerevisiae modulates its membrane lipid composition in a temperature-dependent manner.

Principles and Applications of Biological Membrane Organization.

Many critical biological events, including biochemical signaling, membrane traffic, and cell motility, originate at membrane surfaces. Each such event requires that members of a specific group of proteins and lipids rapidly assemble together at a specific site on the membrane surface. Understanding the biophysical mechanisms that stabilize these assemblies is critical to decoding and controlling cellular functions. In this article, we review progress toward a quantitative biophysical understanding of the mechanisms that drive membrane heterogeneity and organization. We begin from a physical perspective, reviewing the fundamental principles and key experimental evidence behind each proposed mechanism. We then shift to a biological perspective, presenting key examples of the role of heterogeneity in biology and asking which physical mechanisms may be responsible. We close with an applied perspective, noting that membrane heterogeneity provides a novel therapeutic target that is being exploited by a growing number of studies at the interface of biology, physics, and engineering.

BAR scaffolds drive membrane fission by crowding disordered domains.

Cellular membranes are continuously remodeled. The crescent-shaped bin-amphiphysin-rvs (BAR) domains remodel membranes in multiple cellular pathways. Based on studies of isolated BAR domains in vitro, the current paradigm is that BAR domain-containing proteins polymerize into cylindrical scaffolds that stabilize lipid tubules. But in nature, proteins that contain BAR domains often also contain large intrinsically disordered regions. Using in vitro and live cell assays, here we show that full-length BAR domain-containing proteins, rather than stabilizing membrane tubules, are instead surprisingly potent drivers of membrane fission. Specifically, when BAR scaffolds assemble at membrane surfaces, their bulky disordered domains become crowded, generating steric pressure that destabilizes lipid tubules. More broadly, we observe this behavior with BAR domains that have a range of curvatures. These data suggest that the ability to concentrate disordered domains is a key driver of membrane remodeling and fission by BAR domain-containing proteins.

Scaling relationships for translational diffusion constants applied to membrane domain dissolution and growth.

We compare the way that relationships for diffusion constants scale with the size of diffusing membrane domains and the geometry of their environments. Then, we review our experimental work on the dynamics of dissolution/growth of membrane domains in crowding induced mixing, phase separation, and Ostwald ripening in a highly confined environment. Overall, the scaling relationships applied to diffusion constants obtained by fits to our dynamic data indicate that dissolution and growth is influenced by the diffusion of clusters or small domains of lipids, in addition to kinetic processes and geometrical constraints.

Synergy between intrinsically disordered domains and structured proteins amplifies membrane curvature sensing.

The ability of proteins to sense membrane curvature is essential to cellular function. All known sensing mechanisms rely on protein domains with specific structural features such as wedge-like amphipathic helices and crescent-shaped BAR domains. Yet many proteins that contain these domains also contain large intrinsically disordered regions. Here we report that disordered domains are themselves potent sensors of membrane curvature. Comparison of Monte Carlo simulations with in vitro and live-cell measurements demonstrates that the polymer-like behavior of disordered domains found in endocytic proteins drives them to partition preferentially to convex membrane surfaces, which place fewer geometric constraints on their conformational entropy. Further, proteins containing both structured curvature sensors and disordered regions are more than twice as curvature sensitive as their respective structured domains alone. These findings demonstrate an entropic mechanism of curvature sensing that is independent of protein structure and illustrate how structured and disordered domains can synergistically enhance curvature sensitivity.

Dynamics of Crowding-Induced Mixing in Phase Separated Lipid Bilayers.

We use fluorescence microscopy to examine the dynamics of the crowding-induced mixing transition of liquid ordered (Lo)-liquid disordered (Ld) phase separated lipid bilayers when the following particles of increasing size bind to either the Lo or Ld phase: Ubiquitin, green fluorescent protein (GFP), and nanolipoprotein particles (NLPs) of two diameters. These proteinaceous particles contained histidine-tags, which were phase targeted by binding to iminodiacetic acid (IDA) head groups, via a Cu2+ chelating mechanism, of lipids that specifically partition into either the Lo phase or Ld phase. The degree of steric pressure was controlled by varying the size of the bound particle (10-240 kDa) and the amount of binding sites present (i.e., DPIDA concentrations of 9 and 12 mol%) in the supported lipid multibilayer platform used here. We develop a mass transfer-based diffusional model to analyze the observed Lo phase domain dissolution that, along with visual observations and activation energy calculations, provides insight into the sequence of events in crowding-induced mixing. Our results suggest that the degree of steric pressure and target phase influence not only the efficacy of steric-pressure induced mixing, but the rate and controlling mechanism for which it occurs.

Spectroscopic Characterization of Structural Changes in Membrane Scaffold Proteins Entrapped within Mesoporous Silica Gel Monoliths.

The changes in the orientation and conformation of three different membrane scaffold proteins (MSPs) upon entrapment in sol-gel-derived mesoporous silica monoliths were investigated. MSPs were examined in either a lipid-free or a lipid-bound conformation, where the proteins were associated with lipids to form nanolipoprotein particles (NLPs). NLPs are water-soluble, disk-shaped patches of a lipid bilayer that have amphiphilic MSPs shielding the hydrophobic lipid tails. The NLPs in this work had an average thickness of 5 nm and diameters of 9.2, 9.7, and 14.8 nm. We have previously demonstrated that NLPs are more suitable lipid-based structures for silica gel entrapment than liposomes because of their size compatibility with the mesoporous network (2-50 nm) and minimally altered structure after encapsulation. Here we further elaborate on that work by using a variety of spectroscopic techniques to elucidate whether or not different MSPs maintain their protein-lipid interactions after encapsulation. Fluorescence spectroscopy and quenching of the tryptophan residues with acrylamide, 5-DOXYL-stearic acid, and 16-DOXYL-stearic acid were used to determine the MSP orientation. We also utilized fluorescence anisotropy of tryptophans to measure the relative size of the NLPs and MSP aggregates after entrapment. Finally, circular dichroism spectroscopy was used to examine the secondary structure of the MSPs. Our results showed that, after entrapment, all of the lipid-bound MSPs maintained orientations that were minimally changed and indicative of association with lipids in NLPs. The tryptophan residues appeared to remain buried within the hydrophobic core of the lipid tails in the NLPs and appropriately spaced from the bilayer center. Also, after entrapment, lipid-bound MSPs maintained a high degree of α-helical content, a secondary structure associated with protein-lipid interactions. These findings demonstrate that NLPs are capable of serving as viable hosts for functional integral membrane proteins in the synthesis of sol-gel-derived bioinorganic hybrid nanomaterials.